{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}\\cap\coombs\IPS1\redirections\u5390570\Desktop\Australian Public Opinion and Foreign Policy\Public Opinion on China Paper\IRAP Resubmission\Reanalysis of the Results.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}20 Oct 2015, 14:24:20

{com}. ***First with the old RHS variables***

. global xlist1 outgroup_h export_prop

. global xlist2 outgroup_h export_prop H15 B8OWN Age H8 degree

. global xlist3 outgroup_h export_prop H15 B8OWN Age H8 degree min_occ inter1

. melogit china_threat $xlist1* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2442.4962}  
Iteration 1:{space 3}log likelihood = {res:-2440.5202}  
Iteration 2:{space 3}log likelihood = {res:-2440.5193}  
Iteration 3:{space 3}log likelihood = {res:-2440.5193}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2521.5959}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2521.5959}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2444.5951}  
Iteration 2:{space 3}log likelihood = {res:-2440.9874}  
Iteration 3:{space 3}log likelihood = {res:-2440.6671}  
Iteration 4:{space 3}log likelihood = {res:-2440.5279}  
Iteration 5:{space 3}log likelihood = {res:-2440.5231}  (backed up)
Iteration 6:{space 3}log likelihood = {res:-2440.5229}  (backed up)
Iteration 7:{space 3}log likelihood = {res:-2440.5227}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-2440.5227}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2440.5227}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 14:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 17:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 29:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 30:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 31:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 33:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 34:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2440.5227}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2440.5227}  (backed up)
Iteration 40:{space 2}log likelihood = {res:-2440.5226}  (backed up)
Iteration 41:{space 2}log likelihood = {res:-2440.5225}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2440.5225}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2440.5225}  
Iteration 44:{space 2}log likelihood = {res:-2440.5211}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2440.5211}  (not concave)
Iteration 46:{space 2}log likelihood = {res: -2440.521}  (not concave)
Iteration 47:{space 2}log likelihood = {res: -2440.521}  (not concave)
Iteration 48:{space 2}log likelihood = {res: -2440.521}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2440.5209}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-2440.5209}  
Iteration 51:{space 2}log likelihood = {res:-2440.5193}  
Iteration 52:{space 2}log likelihood = {res:-2440.5193}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-2440.5193}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-2440.5193}  (not concave)
Iteration 55:{space 2}log likelihood = {res:-2440.5193}  (backed up)
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3627
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     24.2
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   138.87
{txt}Log likelihood = {res}-2440.5193{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} china_threat{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2} .1872145{col 27}{space 2} .0158867{col 38}{space 1}   11.78{col 47}{space 3}0.000{col 55}{space 4} .1560771{col 68}{space 3}  .218352
{txt}{space 2}export_prop {c |}{col 15}{res}{space 2}-2.735652{col 27}{space 2} 1.403788{col 38}{space 1}   -1.95{col 47}{space 3}0.051{col 55}{space 4}-5.487027{col 68}{space 3} .0157224
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .0509672{col 27}{space 2} .0438361{col 38}{space 1}    1.16{col 47}{space 3}0.245{col 55}{space 4}  -.03495{col 68}{space 3} .1368844
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 2.75e-34{col 27}{space 2} 8.91e-18{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. melogit china_threat $xlist2* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2028.1999}  
Iteration 1:{space 3}log likelihood = {res:-2026.5353}  
Iteration 2:{space 3}log likelihood = {res:-2026.5344}  
Iteration 3:{space 3}log likelihood = {res:-2026.5344}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2094.7355}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2094.7355}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2036.7225}  
Iteration 2:{space 3}log likelihood = {res:-2028.1203}  
Iteration 3:{space 3}log likelihood = {res:-2026.5965}  
Iteration 4:{space 3}log likelihood = {res:-2026.5482}  
Iteration 5:{space 3}log likelihood = {res:-2026.5374}  
Iteration 6:{space 3}log likelihood = {res:-2026.5349}  
Iteration 7:{space 3}log likelihood = {res:-2026.5347}  
Iteration 8:{space 3}log likelihood = {res:-2026.5347}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2026.5347}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 29:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 34:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 36:{space 2}log likelihood = {res:-2026.5347}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2026.5347}  (backed up)
Iteration 38:{space 2}log likelihood = {res:-2026.5346}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2026.5346}  
Iteration 40:{space 2}log likelihood = {res:-2026.5346}  
Iteration 41:{space 2}log likelihood = {res:-2026.5344}  
Iteration 42:{space 2}log likelihood = {res:-2026.5344}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2026.5344}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2026.5344}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2026.5344}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2026.5344}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-2026.5344}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2026.5344}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2026.5344}  (backed up)
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3026
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     20.2
{col 64}{txt}max{col 68}={res}{col 70}       33

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   132.35
{txt}Log likelihood = {res}-2026.5344{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} china_threat{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2} .1895384{col 27}{space 2} .0196276{col 38}{space 1}    9.66{col 47}{space 3}0.000{col 55}{space 4} .1510691{col 68}{space 3} .2280078
{txt}{space 2}export_prop {c |}{col 15}{res}{space 2}-2.474271{col 27}{space 2} 1.555421{col 38}{space 1}   -1.59{col 47}{space 3}0.112{col 55}{space 4} -5.52284{col 68}{space 3} .5742984
{txt}{space 10}H15 {c |}{col 15}{res}{space 2}-.0150098{col 27}{space 2} .0066307{col 38}{space 1}   -2.26{col 47}{space 3}0.024{col 55}{space 4}-.0280057{col 68}{space 3}-.0020138
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2} .0416542{col 27}{space 2}  .017657{col 38}{space 1}    2.36{col 47}{space 3}0.018{col 55}{space 4} .0070472{col 68}{space 3} .0762612
{txt}{space 10}Age {c |}{col 15}{res}{space 2}-.0040574{col 27}{space 2} .0025925{col 38}{space 1}   -1.57{col 47}{space 3}0.118{col 55}{space 4}-.0091387{col 68}{space 3} .0010239
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0178369{col 27}{space 2} .0511715{col 38}{space 1}   -0.35{col 47}{space 3}0.727{col 55}{space 4}-.1181312{col 68}{space 3} .0824574
{txt}{space 7}degree {c |}{col 15}{res}{space 2} .1738751{col 27}{space 2}  .089621{col 38}{space 1}    1.94{col 47}{space 3}0.052{col 55}{space 4}-.0017789{col 68}{space 3} .3495291
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .2342548{col 27}{space 2} .1949419{col 38}{space 1}    1.20{col 47}{space 3}0.229{col 55}{space 4}-.1478242{col 68}{space 3} .6163339
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 2.16e-34{col 27}{space 2} 1.46e-18{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. melogit china_threat $xlist3* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res: -2026.601}  
Iteration 1:{space 3}log likelihood = {res:-2024.9222}  
Iteration 2:{space 3}log likelihood = {res:-2024.9213}  
Iteration 3:{space 3}log likelihood = {res:-2024.9213}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2092.8279}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2092.8279}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2034.9441}  
Iteration 2:{space 3}log likelihood = {res:-2026.8642}  
Iteration 3:{space 3}log likelihood = {res:-2024.9598}  
Iteration 4:{space 3}log likelihood = {res:-2024.9305}  
Iteration 5:{space 3}log likelihood = {res:-2024.9213}  
Iteration 6:{space 3}log likelihood = {res:-2024.9213}  
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3026
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     20.2
{col 64}{txt}max{col 68}={res}{col 70}       33

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}9{txt}){col 68}={res}{col 70}   134.49
{txt}Log likelihood = {res}-2024.9213{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} china_threat{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2} .1903896{col 27}{space 2} .0196967{col 38}{space 1}    9.67{col 47}{space 3}0.000{col 55}{space 4} .1517848{col 68}{space 3} .2289945
{txt}{space 2}export_prop {c |}{col 15}{res}{space 2}-3.393963{col 27}{space 2} 1.824972{col 38}{space 1}   -1.86{col 47}{space 3}0.063{col 55}{space 4}-6.970843{col 68}{space 3} .1829164
{txt}{space 10}H15 {c |}{col 15}{res}{space 2}-.0141031{col 27}{space 2} .0066924{col 38}{space 1}   -2.11{col 47}{space 3}0.035{col 55}{space 4}-.0272199{col 68}{space 3}-.0009863
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2} .0421254{col 27}{space 2} .0176953{col 38}{space 1}    2.38{col 47}{space 3}0.017{col 55}{space 4} .0074433{col 68}{space 3} .0768076
{txt}{space 10}Age {c |}{col 15}{res}{space 2}-.0040027{col 27}{space 2} .0025952{col 38}{space 1}   -1.54{col 47}{space 3}0.123{col 55}{space 4}-.0090891{col 68}{space 3} .0010838
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0164098{col 27}{space 2}  .051217{col 38}{space 1}   -0.32{col 47}{space 3}0.749{col 55}{space 4}-.1167932{col 68}{space 3} .0839735
{txt}{space 7}degree {c |}{col 15}{res}{space 2}  .164158{col 27}{space 2} .0899976{col 38}{space 1}    1.82{col 47}{space 3}0.068{col 55}{space 4} -.012234{col 68}{space 3}   .34055
{txt}{space 6}min_occ {c |}{col 15}{res}{space 2}-.1871516{col 27}{space 2} .1052895{col 38}{space 1}   -1.78{col 47}{space 3}0.075{col 55}{space 4}-.3935153{col 68}{space 3} .0192121
{txt}{space 7}inter1 {c |}{col 15}{res}{space 2} 3.104128{col 27}{space 2} 3.418677{col 38}{space 1}    0.91{col 47}{space 3}0.364{col 55}{space 4}-3.596355{col 68}{space 3} 9.804611
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .2738966{col 27}{space 2} .1966863{col 38}{space 1}    1.39{col 47}{space 3}0.164{col 55}{space 4}-.1116014{col 68}{space 3} .6593946
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} .0002421{col 27}{space 2} .0230246{col 55}{space 4} 2.71e-85{col 68}{space 3} 2.17e+77
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 34}{txt}{help j_chibar##|_new:chibar2(01) =}{res}{col 48} 1.1e-04{col 57}{txt}Prob>=chibar2 = {res}{col 73}0.4958

{com}. ****The interaction term is not only not significant but points in the 'wrong' direction. Being in a mining occupation would seem to negate the effect of being in an exporting district***

. ***Now re-running this analysis with ordered logit***

. ***F5CHINA=1 if respondent believes China to be a 'very likely' threat etc. Hence negative coefficient means you are more likely to view China as threatening**

. meologit F5CHINA $xlist1* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-3481.5703}  
Iteration 1:{space 3}log likelihood = {res:-3368.1253}  
Iteration 2:{space 3}log likelihood = {res:-3367.6376}  
Iteration 3:{space 3}log likelihood = {res:-3367.6374}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-3458.5892}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-3458.5892}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-3412.6264}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-3371.5953}  
Iteration 3:{space 3}log likelihood = {res:-3369.3208}  
Iteration 4:{space 3}log likelihood = {res:-3367.8284}  
Iteration 5:{space 3}log likelihood = {res:-3367.7185}  
Iteration 6:{space 3}log likelihood = {res:-3367.6951}  (backed up)
Iteration 7:{space 3}log likelihood = {res:-3367.6839}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-3367.6784}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-3367.6756}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-3367.6753}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-3367.6751}  (backed up)
Iteration 12:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 13:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 14:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 15:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 16:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 17:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 18:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 19:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 20:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 21:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 22:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 23:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 24:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 25:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 26:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 27:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 28:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 29:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 30:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 31:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 32:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 33:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 34:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 35:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 36:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 37:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 38:{space 2}log likelihood = {res: -3367.675}  (not concave)
Iteration 39:{space 2}log likelihood = {res: -3367.675}  (backed up)
Iteration 40:{space 2}log likelihood = {res:-3367.6749}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-3367.6749}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-3367.6748}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-3367.6748}  
Iteration 44:{space 2}log likelihood = {res:-3367.6743}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-3367.6742}  
Iteration 46:{space 2}log likelihood = {res:-3367.6582}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-3367.6581}  
Iteration 48:{space 2}log likelihood = {res:-3367.6374}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-3367.6374}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3539
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     23.6
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   216.25
{txt}Log likelihood = {res}-3367.6374{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      F5CHINA{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2}-.2292639{col 27}{space 2} .0155984{col 38}{space 1}  -14.70{col 47}{space 3}0.000{col 55}{space 4}-.2598362{col 68}{space 3}-.1986916
{txt}{space 2}export_prop {c |}{col 15}{res}{space 2} 2.828195{col 27}{space 2} 1.365671{col 38}{space 1}    2.07{col 47}{space 3}0.038{col 55}{space 4} .1515297{col 68}{space 3} 5.504861
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2}-1.914811{col 27}{space 2} .0571941{col 38}{space 1}  -33.48{col 47}{space 3}0.000{col 55}{space 4} -2.02691{col 68}{space 3}-1.802713
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2} .1186686{col 27}{space 2} .0437453{col 38}{space 1}    2.71{col 47}{space 3}0.007{col 55}{space 4} .0329294{col 68}{space 3} .2044077
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 9.11e-32{col 27}{space 2} 6.08e-17{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***Proportion of exporters is significant here***

. meologit F5CHINA $xlist2* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2917.5184}  
Iteration 1:{space 3}log likelihood = {res:-2815.3093}  
Iteration 2:{space 3}log likelihood = {res:-2814.8126}  
Iteration 3:{space 3}log likelihood = {res:-2814.8124}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2892.5971}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2892.5971}  (not concave)
Iteration 1:{space 3}log likelihood = {res:  -2856.39}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2822.9237}  
Iteration 3:{space 3}log likelihood = {res:-2815.3995}  
Iteration 4:{space 3}log likelihood = {res:-2815.0204}  
Iteration 5:{space 3}log likelihood = {res:-2814.9284}  
Iteration 6:{space 3}log likelihood = {res:-2814.8939}  
Iteration 7:{space 3}log likelihood = {res:-2814.8788}  
Iteration 8:{space 3}log likelihood = {res:-2814.8752}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2814.8743}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2814.8739}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2814.8739}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 35:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 36:{space 2}log likelihood = {res:-2814.8738}  (backed up)
Iteration 37:{space 2}log likelihood = {res:-2814.8738}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2814.8738}  
Iteration 39:{space 2}log likelihood = {res:-2814.8733}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2814.8732}  
Iteration 41:{space 2}log likelihood = {res:-2814.8727}  (not concave)
Iteration 42:{space 2}log likelihood = {res: -2814.872}  
Iteration 43:{space 2}log likelihood = {res:-2814.8717}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2814.8708}  
Iteration 45:{space 2}log likelihood = {res:-2814.8125}  
Iteration 46:{space 2}log likelihood = {res:-2814.8124}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-2814.8124}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2814.8124}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     2974
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     19.8
{col 64}{txt}max{col 68}={res}{col 70}       30

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   193.51
{txt}Log likelihood = {res}-2814.8124{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      F5CHINA{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2}-.2191313{col 27}{space 2} .0190117{col 38}{space 1}  -11.53{col 47}{space 3}0.000{col 55}{space 4}-.2563935{col 68}{space 3}-.1818691
{txt}{space 2}export_prop {c |}{col 15}{res}{space 2} 1.990903{col 27}{space 2} 1.508493{col 38}{space 1}    1.32{col 47}{space 3}0.187{col 55}{space 4}-.9656892{col 68}{space 3} 4.947495
{txt}{space 10}H15 {c |}{col 15}{res}{space 2} .0238079{col 27}{space 2} .0064095{col 38}{space 1}    3.71{col 47}{space 3}0.000{col 55}{space 4} .0112455{col 68}{space 3} .0363704
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2}-.0435235{col 27}{space 2} .0170967{col 38}{space 1}   -2.55{col 47}{space 3}0.011{col 55}{space 4}-.0770325{col 68}{space 3}-.0100145
{txt}{space 10}Age {c |}{col 15}{res}{space 2} .0052843{col 27}{space 2} .0024956{col 38}{space 1}    2.12{col 47}{space 3}0.034{col 55}{space 4} .0003931{col 68}{space 3} .0101755
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0042149{col 27}{space 2} .0494097{col 38}{space 1}   -0.09{col 47}{space 3}0.932{col 55}{space 4}-.1010562{col 68}{space 3} .0926264
{txt}{space 7}degree {c |}{col 15}{res}{space 2}-.1937392{col 27}{space 2}  .085658{col 38}{space 1}   -2.26{col 47}{space 3}0.024{col 55}{space 4}-.3616258{col 68}{space 3}-.0258526
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2}-1.653431{col 27}{space 2} .1926322{col 38}{space 1}   -8.58{col 47}{space 3}0.000{col 55}{space 4}-2.030983{col 68}{space 3}-1.275879
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2} .3867049{col 27}{space 2} .1896698{col 38}{space 1}    2.04{col 47}{space 3}0.041{col 55}{space 4} .0149589{col 68}{space 3} .7584509
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 6.03e-33{col 27}{space 2} 7.74e-18{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48} 9.0e-11{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***Not if you include any controls***

. meologit F5CHINA $xlist3* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2917.5184}  
Iteration 1:{space 3}log likelihood = {res:-2813.1417}  
Iteration 2:{space 3}log likelihood = {res:-2812.6247}  
Iteration 3:{space 3}log likelihood = {res:-2812.6245}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2890.2972}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2890.2972}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2854.1305}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2820.7113}  
Iteration 3:{space 3}log likelihood = {res:-2813.2605}  
Iteration 4:{space 3}log likelihood = {res:-2812.8569}  
Iteration 5:{space 3}log likelihood = {res:-2812.7601}  
Iteration 6:{space 3}log likelihood = {res:-2812.6901}  
Iteration 7:{space 3}log likelihood = {res:-2812.6834}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-2812.6817}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2812.6809}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2812.6808}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 27:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 28:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 31:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 35:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 37:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 39:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 40:{space 2}log likelihood = {res:-2812.6807}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2812.6807}  (backed up)
Iteration 42:{space 2}log likelihood = {res:-2812.6806}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2812.6806}  
Iteration 44:{space 2}log likelihood = {res:-2812.6806}  (backed up)
Iteration 45:{space 2}log likelihood = {res:-2812.6797}  (backed up)
Iteration 46:{space 2}log likelihood = {res:-2812.6763}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-2812.6756}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2812.6746}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2812.6737}  
Iteration 50:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 55:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 56:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 57:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 58:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 59:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 60:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 61:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 62:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 63:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 64:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 65:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 66:{space 2}log likelihood = {res:-2812.6245}  (not concave)
Iteration 67:{space 2}log likelihood = {res:-2812.6245}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     2974
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     19.8
{col 64}{txt}max{col 68}={res}{col 70}       30

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}9{txt}){col 68}={res}{col 70}   197.58
{txt}Log likelihood = {res}-2812.6245{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      F5CHINA{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2}-.2196084{col 27}{space 2} .0190415{col 38}{space 1}  -11.53{col 47}{space 3}0.000{col 55}{space 4}-.2569291{col 68}{space 3}-.1822877
{txt}{space 2}export_prop {c |}{col 15}{res}{space 2}  3.39392{col 27}{space 2} 1.766178{col 38}{space 1}    1.92{col 47}{space 3}0.055{col 55}{space 4}-.0677243{col 68}{space 3} 6.855565
{txt}{space 10}H15 {c |}{col 15}{res}{space 2} .0230706{col 27}{space 2} .0064515{col 38}{space 1}    3.58{col 47}{space 3}0.000{col 55}{space 4} .0104259{col 68}{space 3} .0357153
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2}-.0440783{col 27}{space 2}  .017117{col 38}{space 1}   -2.58{col 47}{space 3}0.010{col 55}{space 4} -.077627{col 68}{space 3}-.0105296
{txt}{space 10}Age {c |}{col 15}{res}{space 2} .0051832{col 27}{space 2}  .002497{col 38}{space 1}    2.08{col 47}{space 3}0.038{col 55}{space 4} .0002891{col 68}{space 3} .0100773
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0052767{col 27}{space 2} .0494436{col 38}{space 1}   -0.11{col 47}{space 3}0.915{col 55}{space 4}-.1021843{col 68}{space 3}  .091631
{txt}{space 7}degree {c |}{col 15}{res}{space 2} -.185283{col 27}{space 2} .0859531{col 38}{space 1}   -2.16{col 47}{space 3}0.031{col 55}{space 4} -.353748{col 68}{space 3}-.0168179
{txt}{space 6}min_occ {c |}{col 15}{res}{space 2} .2101426{col 27}{space 2} .1013352{col 38}{space 1}    2.07{col 47}{space 3}0.038{col 55}{space 4} .0115292{col 68}{space 3}  .408756
{txt}{space 7}inter1 {c |}{col 15}{res}{space 2}-4.911066{col 27}{space 2} 3.321301{col 38}{space 1}   -1.48{col 47}{space 3}0.139{col 55}{space 4} -11.4207{col 68}{space 3} 1.598564
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2}-1.610323{col 27}{space 2} .1937107{col 38}{space 1}   -8.31{col 47}{space 3}0.000{col 55}{space 4}-1.989989{col 68}{space 3}-1.230657
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2} .4321243{col 27}{space 2} .1909481{col 38}{space 1}    2.26{col 47}{space 3}0.024{col 55}{space 4}  .057873{col 68}{space 3} .8063756
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 2.14e-42{col 27}{space 2} 1.03e-23{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***Again, interaction effect is the same - it works in the opposite direction to that expected***

. ***Using Mining as a Proportion of Division Employment***

. global xlist_1 outgroup_h mining_prop

. global xlist_2 outgroup_h mining_prop H15 B8OWN Age H8 degree

. global xlist_3 outgroup_h mining_prop H15 B8OWN Age H8 degree min_occ inter1

. melogit china_threat $xlist_1* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2444.3812}  
Iteration 1:{space 3}log likelihood = {res:-2442.4235}  
Iteration 2:{space 3}log likelihood = {res:-2442.4227}  
Iteration 3:{space 3}log likelihood = {res:-2442.4227}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2522.0947}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2522.0947}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2445.7084}  
Iteration 2:{space 3}log likelihood = {res:-2443.1315}  
Iteration 3:{space 3}log likelihood = {res:-2442.4657}  
Iteration 4:{space 3}log likelihood = {res:-2442.4298}  
Iteration 5:{space 3}log likelihood = {res:-2442.4272}  
Iteration 6:{space 3}log likelihood = {res:-2442.4259}  (backed up)
Iteration 7:{space 3}log likelihood = {res:-2442.4253}  (backed up)
Iteration 8:{space 3}log likelihood = {res: -2442.425}  (backed up)
Iteration 9:{space 3}log likelihood = {res: -2442.425}  (backed up)
Iteration 10:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 11:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 12:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 13:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 14:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 15:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 16:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 17:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 18:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 19:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 20:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 21:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 22:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 23:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 24:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 25:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 26:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 27:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 28:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 29:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 30:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 31:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 32:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 33:{space 2}log likelihood = {res: -2442.425}  (backed up)
Iteration 34:{space 2}log likelihood = {res: -2442.425}  (not concave)
Iteration 35:{space 2}log likelihood = {res: -2442.425}  
Iteration 36:{space 2}log likelihood = {res:-2442.4248}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2442.4248}  
Iteration 38:{space 2}log likelihood = {res:-2442.4248}  (backed up)
Iteration 39:{space 2}log likelihood = {res:-2442.4239}  
Iteration 40:{space 2}log likelihood = {res:-2442.4239}  (backed up)
Iteration 41:{space 2}log likelihood = {res:-2442.4227}  
Iteration 42:{space 2}log likelihood = {res:-2442.4227}  
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3627
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     24.2
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   135.48
{txt}Log likelihood = {res}-2442.4227{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} china_threat{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2} .1822838{col 27}{space 2} .0157757{col 38}{space 1}   11.55{col 47}{space 3}0.000{col 55}{space 4} .1513641{col 68}{space 3} .2132036
{txt}{space 2}mining_prop {c |}{col 15}{res}{space 2} -.062156{col 27}{space 2} 2.908689{col 38}{space 1}   -0.02{col 47}{space 3}0.983{col 55}{space 4}-5.763081{col 68}{space 3} 5.638769
{txt}{space 8}_cons {c |}{col 15}{res}{space 2}-.0027525{col 27}{space 2} .0404314{col 38}{space 1}   -0.07{col 47}{space 3}0.946{col 55}{space 4}-.0819967{col 68}{space 3} .0764917
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 5.08e-31{col 27}{space 2} 2.97e-16{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***Insignificant even with only one control***

. melogit china_threat $xlist_2* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2029.3562}  
Iteration 1:{space 3}log likelihood = {res:-2027.7058}  
Iteration 2:{space 3}log likelihood = {res:-2027.7049}  
Iteration 3:{space 3}log likelihood = {res:-2027.7049}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2095.1844}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2095.1844}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2037.2878}  
Iteration 2:{space 3}log likelihood = {res:-2030.3939}  
Iteration 3:{space 3}log likelihood = {res:-2028.4729}  
Iteration 4:{space 3}log likelihood = {res:-2027.7857}  
Iteration 5:{space 3}log likelihood = {res:-2027.7007}  
Iteration 6:{space 3}log likelihood = {res:-2027.6999}  
Iteration 7:{space 3}log likelihood = {res:-2027.6999}  
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3026
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     20.2
{col 64}{txt}max{col 68}={res}{col 70}       33

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   129.19
{txt}Log likelihood = {res}-2027.6999{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} china_threat{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2} .1867748{col 27}{space 2} .0196322{col 38}{space 1}    9.51{col 47}{space 3}0.000{col 55}{space 4} .1482965{col 68}{space 3} .2252532
{txt}{space 2}mining_prop {c |}{col 15}{res}{space 2}-1.425507{col 27}{space 2} 3.231635{col 38}{space 1}   -0.44{col 47}{space 3}0.659{col 55}{space 4}-7.759396{col 68}{space 3} 4.908381
{txt}{space 10}H15 {c |}{col 15}{res}{space 2} -.014486{col 27}{space 2} .0066476{col 38}{space 1}   -2.18{col 47}{space 3}0.029{col 55}{space 4} -.027515{col 68}{space 3} -.001457
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2} .0412936{col 27}{space 2} .0176612{col 38}{space 1}    2.34{col 47}{space 3}0.019{col 55}{space 4} .0066783{col 68}{space 3}  .075909
{txt}{space 10}Age {c |}{col 15}{res}{space 2}-.0040908{col 27}{space 2} .0025929{col 38}{space 1}   -1.58{col 47}{space 3}0.115{col 55}{space 4}-.0091728{col 68}{space 3} .0009913
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0192047{col 27}{space 2} .0511767{col 38}{space 1}   -0.38{col 47}{space 3}0.707{col 55}{space 4}-.1195091{col 68}{space 3} .0810998
{txt}{space 7}degree {c |}{col 15}{res}{space 2} .1784479{col 27}{space 2} .0897069{col 38}{space 1}    1.99{col 47}{space 3}0.047{col 55}{space 4} .0026257{col 68}{space 3} .3542702
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .1951146{col 27}{space 2} .1939664{col 38}{space 1}    1.01{col 47}{space 3}0.314{col 55}{space 4}-.1850525{col 68}{space 3} .5752817
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} .0023215{col 27}{space 2} .0232911{col 55}{space 4} 6.70e-12{col 68}{space 3} 804763.4
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 34}{txt}{help j_chibar##|_new:chibar2(01) =}{res}{col 48}    0.01{col 57}{txt}Prob>=chibar2 = {res}{col 73}0.4600

{com}. melogit china_threat $xlist_3* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2028.2132}  
Iteration 1:{space 3}log likelihood = {res:-2026.5473}  
Iteration 2:{space 3}log likelihood = {res:-2026.5464}  
Iteration 3:{space 3}log likelihood = {res:-2026.5464}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2093.6854}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2093.6854}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2035.9046}  
Iteration 2:{space 3}log likelihood = {res:-2029.4823}  
Iteration 3:{space 3}log likelihood = {res:-2027.3205}  
Iteration 4:{space 3}log likelihood = {res:-2026.6243}  
Iteration 5:{space 3}log likelihood = {res:-2026.5363}  
Iteration 6:{space 3}log likelihood = {res:-2026.5355}  
Iteration 7:{space 3}log likelihood = {res:-2026.5355}  
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3026
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     20.2
{col 64}{txt}max{col 68}={res}{col 70}       33

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}9{txt}){col 68}={res}{col 70}   131.15
{txt}Log likelihood = {res}-2026.5355{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} china_threat{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2} .1880833{col 27}{space 2} .0196975{col 38}{space 1}    9.55{col 47}{space 3}0.000{col 55}{space 4} .1494768{col 68}{space 3} .2266898
{txt}{space 2}mining_prop {c |}{col 15}{res}{space 2}-1.660399{col 27}{space 2} 3.503588{col 38}{space 1}   -0.47{col 47}{space 3}0.636{col 55}{space 4}-8.527305{col 68}{space 3} 5.206507
{txt}{space 10}H15 {c |}{col 15}{res}{space 2}-.0133862{col 27}{space 2} .0066913{col 38}{space 1}   -2.00{col 47}{space 3}0.045{col 55}{space 4}-.0265009{col 68}{space 3}-.0002715
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2} .0410529{col 27}{space 2} .0176894{col 38}{space 1}    2.32{col 47}{space 3}0.020{col 55}{space 4} .0063824{col 68}{space 3} .0757235
{txt}{space 10}Age {c |}{col 15}{res}{space 2}-.0040729{col 27}{space 2} .0025954{col 38}{space 1}   -1.57{col 47}{space 3}0.117{col 55}{space 4}-.0091597{col 68}{space 3} .0010139
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0173328{col 27}{space 2} .0512242{col 38}{space 1}   -0.34{col 47}{space 3}0.735{col 55}{space 4}-.1177303{col 68}{space 3} .0830648
{txt}{space 7}degree {c |}{col 15}{res}{space 2} .1682702{col 27}{space 2} .0900141{col 38}{space 1}    1.87{col 47}{space 3}0.062{col 55}{space 4}-.0081542{col 68}{space 3} .3446946
{txt}{space 6}min_occ {c |}{col 15}{res}{space 2}-.1330407{col 27}{space 2} .1021723{col 38}{space 1}   -1.30{col 47}{space 3}0.193{col 55}{space 4}-.3332946{col 68}{space 3} .0672133
{txt}{space 7}inter1 {c |}{col 15}{res}{space 2} .3869695{col 27}{space 2}  3.16914{col 38}{space 1}    0.12{col 47}{space 3}0.903{col 55}{space 4}-5.824431{col 68}{space 3}  6.59837
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .2204111{col 27}{space 2} .1949659{col 38}{space 1}    1.13{col 47}{space 3}0.258{col 55}{space 4}-.1617149{col 68}{space 3} .6025372
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} .0034453{col 27}{space 2} .0235644{col 55}{space 4} 5.19e-09{col 68}{space 3} 2286.305
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 34}{txt}{help j_chibar##|_new:chibar2(01) =}{res}{col 48}    0.02{col 57}{txt}Prob>=chibar2 = {res}{col 73}0.4411

{com}. ***Again, the interaction term points in the 'wrong' direction***

. ***Now with ordered logit***

. meologit F5CHINA $xlist_1* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-3481.5703}  
Iteration 1:{space 3}log likelihood = {res:-3370.1946}  
Iteration 2:{space 3}log likelihood = {res:-3369.7295}  
Iteration 3:{space 3}log likelihood = {res:-3369.7294}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-3459.0493}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-3459.0493}  (not concave)
Iteration 1:{space 3}log likelihood = {res: -3413.119}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-3372.7339}  
Iteration 3:{space 3}log likelihood = {res:-3370.1996}  
Iteration 4:{space 3}log likelihood = {res: -3369.781}  
Iteration 5:{space 3}log likelihood = {res:-3369.7684}  (backed up)
Iteration 6:{space 3}log likelihood = {res:-3369.7623}  (backed up)
Iteration 7:{space 3}log likelihood = {res:-3369.7608}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-3369.7607}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-3369.7607}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 27:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 28:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 29:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 30:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-3369.7607}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 38:{space 2}log likelihood = {res:-3369.7607}  (backed up)
Iteration 39:{space 2}log likelihood = {res:-3369.7606}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-3369.7606}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-3369.7606}  
Iteration 42:{space 2}log likelihood = {res:-3369.7603}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-3369.7603}  
Iteration 44:{space 2}log likelihood = {res:-3369.7584}  
Iteration 45:{space 2}log likelihood = {res:-3369.7549}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-3369.7547}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-3369.7544}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-3369.7539}  (not concave)
Iteration 49:{space 2}log likelihood = {res: -3369.753}  
Iteration 50:{space 2}log likelihood = {res:-3369.7294}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-3369.7294}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-3369.7294}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-3369.7294}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3539
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     23.6
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   212.57
{txt}Log likelihood = {res}-3369.7294{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      F5CHINA{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2}-.2245723{col 27}{space 2} .0154919{col 38}{space 1}  -14.50{col 47}{space 3}0.000{col 55}{space 4}-.2549358{col 68}{space 3}-.1942089
{txt}{space 2}mining_prop {c |}{col 15}{res}{space 2} 1.040986{col 27}{space 2} 2.797652{col 38}{space 1}    0.37{col 47}{space 3}0.710{col 55}{space 4}-4.442312{col 68}{space 3} 6.524283
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2} -1.96094{col 27}{space 2} .0552633{col 38}{space 1}  -35.48{col 47}{space 3}0.000{col 55}{space 4}-2.069254{col 68}{space 3}-1.852625
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2} .0707574{col 27}{space 2} .0405295{col 38}{space 1}    1.75{col 47}{space 3}0.081{col 55}{space 4} -.008679{col 68}{space 3} .1501939
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 6.20e-35{col 27}{space 2} 4.71e-19{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***No difference***

. meologit F5CHINA $xlist_2* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2917.5184}  
Iteration 1:{space 3}log likelihood = {res:-2816.1167}  
Iteration 2:{space 3}log likelihood = {res:-2815.6297}  
Iteration 3:{space 3}log likelihood = {res:-2815.6295}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2892.9175}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2892.9175}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2856.7118}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2823.3345}  
Iteration 3:{space 3}log likelihood = {res: -2816.675}  
Iteration 4:{space 3}log likelihood = {res:-2816.0281}  
Iteration 5:{space 3}log likelihood = {res:-2815.7717}  
Iteration 6:{space 3}log likelihood = {res:-2815.7067}  
Iteration 7:{space 3}log likelihood = {res:-2815.6821}  
Iteration 8:{space 3}log likelihood = {res:-2815.6713}  
Iteration 9:{space 3}log likelihood = {res: -2815.671}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2815.6708}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2815.6708}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 28:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 31:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 33:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 34:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 35:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 37:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 39:{space 2}log likelihood = {res:-2815.6707}  (backed up)
Iteration 40:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2815.6707}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-2815.6707}  
Iteration 51:{space 2}log likelihood = {res:-2815.6705}  (backed up)
Iteration 52:{space 2}log likelihood = {res:-2815.6704}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-2815.6703}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-2815.6702}  
Iteration 55:{space 2}log likelihood = {res:-2815.6696}  (backed up)
Iteration 56:{space 2}log likelihood = {res:-2815.6602}  (not concave)
Iteration 57:{space 2}log likelihood = {res:-2815.6597}  
Iteration 58:{space 2}log likelihood = {res:-2815.6295}  
Iteration 59:{space 2}log likelihood = {res:-2815.6295}  
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     2974
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     19.8
{col 64}{txt}max{col 68}={res}{col 70}       30

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   192.09
{txt}Log likelihood = {res}-2815.6295{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      F5CHINA{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2}-.2166167{col 27}{space 2} .0189653{col 38}{space 1}  -11.42{col 47}{space 3}0.000{col 55}{space 4} -.253788{col 68}{space 3}-.1794453
{txt}{space 2}mining_prop {c |}{col 15}{res}{space 2} 1.054444{col 27}{space 2} 3.091459{col 38}{space 1}    0.34{col 47}{space 3}0.733{col 55}{space 4}-5.004705{col 68}{space 3} 7.113594
{txt}{space 10}H15 {c |}{col 15}{res}{space 2}  .023339{col 27}{space 2}  .006404{col 38}{space 1}    3.64{col 47}{space 3}0.000{col 55}{space 4} .0107874{col 68}{space 3} .0358906
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2}-.0434109{col 27}{space 2} .0170921{col 38}{space 1}   -2.54{col 47}{space 3}0.011{col 55}{space 4}-.0769109{col 68}{space 3}-.0099109
{txt}{space 10}Age {c |}{col 15}{res}{space 2} .0052838{col 27}{space 2} .0024955{col 38}{space 1}    2.12{col 47}{space 3}0.034{col 55}{space 4} .0003928{col 68}{space 3} .0101749
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0031589{col 27}{space 2} .0494081{col 38}{space 1}   -0.06{col 47}{space 3}0.949{col 55}{space 4}-.0999971{col 68}{space 3} .0936793
{txt}{space 7}degree {c |}{col 15}{res}{space 2} -.197807{col 27}{space 2} .0856161{col 38}{space 1}   -2.31{col 47}{space 3}0.021{col 55}{space 4}-.3656114{col 68}{space 3}-.0300025
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2} -1.68776{col 27}{space 2}  .191324{col 38}{space 1}   -8.82{col 47}{space 3}0.000{col 55}{space 4}-2.062748{col 68}{space 3}-1.312772
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2} .3516177{col 27}{space 2} .1882232{col 38}{space 1}    1.87{col 47}{space 3}0.062{col 55}{space 4}-.0172931{col 68}{space 3} .7205284
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 5.68e-32{col 27}{space 2} 3.34e-17{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48} 8.5e-11{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. meologit F5CHINA $xlist_3* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2917.5184}  
Iteration 1:{space 3}log likelihood = {res:-2814.7927}  
Iteration 2:{space 3}log likelihood = {res:-2814.2945}  
Iteration 3:{space 3}log likelihood = {res:-2814.2943}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2891.1193}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2891.1193}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2854.9476}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2821.6761}  
Iteration 3:{space 3}log likelihood = {res:-2815.6543}  
Iteration 4:{space 3}log likelihood = {res:-2814.8127}  
Iteration 5:{space 3}log likelihood = {res:-2814.5062}  
Iteration 6:{space 3}log likelihood = {res: -2814.365}  
Iteration 7:{space 3}log likelihood = {res:-2814.3455}  
Iteration 8:{space 3}log likelihood = {res:-2814.3285}  
Iteration 9:{space 3}log likelihood = {res:-2814.3276}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2814.3273}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 29:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 30:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 31:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 33:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 34:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 35:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2814.3272}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2814.3272}  (backed up)
Iteration 38:{space 2}log likelihood = {res:-2814.3271}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2814.3271}  (not concave)
Iteration 40:{space 2}log likelihood = {res: -2814.327}  (not concave)
Iteration 41:{space 2}log likelihood = {res: -2814.327}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2814.3269}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2814.3264}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2814.3257}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2814.3246}  
Iteration 46:{space 2}log likelihood = {res:-2814.2943}  
Iteration 47:{space 2}log likelihood = {res:-2814.2943}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2814.2943}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     2974
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     19.8
{col 64}{txt}max{col 68}={res}{col 70}       30

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}9{txt}){col 68}={res}{col 70}   194.67
{txt}Log likelihood = {res}-2814.2943{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      F5CHINA{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      z{col 47}   P>|z|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}outgroup_h {c |}{col 15}{res}{space 2}-.2170748{col 27}{space 2} .0190085{col 38}{space 1}  -11.42{col 47}{space 3}0.000{col 55}{space 4}-.2543307{col 68}{space 3}-.1798189
{txt}{space 2}mining_prop {c |}{col 15}{res}{space 2} 2.066383{col 27}{space 2} 3.331432{col 38}{space 1}    0.62{col 47}{space 3}0.535{col 55}{space 4}-4.463104{col 68}{space 3} 8.595871
{txt}{space 10}H15 {c |}{col 15}{res}{space 2} .0222718{col 27}{space 2} .0064439{col 38}{space 1}    3.46{col 47}{space 3}0.001{col 55}{space 4}  .009642{col 68}{space 3} .0349016
{txt}{space 8}B8OWN {c |}{col 15}{res}{space 2}-.0433737{col 27}{space 2} .0171036{col 38}{space 1}   -2.54{col 47}{space 3}0.011{col 55}{space 4}-.0768962{col 68}{space 3}-.0098513
{txt}{space 10}Age {c |}{col 15}{res}{space 2} .0052277{col 27}{space 2} .0024963{col 38}{space 1}    2.09{col 47}{space 3}0.036{col 55}{space 4} .0003352{col 68}{space 3} .0101203
{txt}{space 11}H8 {c |}{col 15}{res}{space 2}-.0043943{col 27}{space 2} .0494334{col 38}{space 1}   -0.09{col 47}{space 3}0.929{col 55}{space 4} -.101282{col 68}{space 3} .0924934
{txt}{space 7}degree {c |}{col 15}{res}{space 2}-.1898451{col 27}{space 2} .0858979{col 38}{space 1}   -2.21{col 47}{space 3}0.027{col 55}{space 4}-.3582019{col 68}{space 3}-.0214883
{txt}{space 6}min_occ {c |}{col 15}{res}{space 2} .1581269{col 27}{space 2} .0979979{col 38}{space 1}    1.61{col 47}{space 3}0.107{col 55}{space 4}-.0339454{col 68}{space 3} .3501993
{txt}{space 7}inter1 {c |}{col 15}{res}{space 2}-2.304804{col 27}{space 2} 3.056842{col 38}{space 1}   -0.75{col 47}{space 3}0.451{col 55}{space 4}-8.296104{col 68}{space 3} 3.686496
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}/cut1 {c |}{col 15}{res}{space 2}-1.663581{col 27}{space 2} .1919082{col 38}{space 1}   -8.67{col 47}{space 3}0.000{col 55}{space 4}-2.039714{col 68}{space 3}-1.287447
{txt}{space 8}/cut2 {c |}{col 15}{res}{space 2} .3773487{col 27}{space 2} .1889276{col 38}{space 1}    2.00{col 47}{space 3}0.046{col 55}{space 4} .0070574{col 68}{space 3} .7476401
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum     {col 15}{c |}
    var(_cons){c |}{col 15}{res}{space 2} 1.14e-33{col 27}{space 2} 1.86e-17{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48} 9.7e-11{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***Now looking at agriculture***

. global xlist_new1 outgroup_h agri_proportion

. global xlist_new2 outgroup_h agri_proportion H15 B8OWN Age H8 degree

. melogit china_threat $xlist_new1* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2441.0698}  
Iteration 1:{space 3}log likelihood = {res:-2439.0842}  
Iteration 2:{space 3}log likelihood = {res:-2439.0834}  
Iteration 3:{space 3}log likelihood = {res:-2439.0834}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2521.3802}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2521.3802}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2443.8587}  
Iteration 2:{space 3}log likelihood = {res:-2439.1658}  
Iteration 3:{space 3}log likelihood = {res:-2439.1173}  
Iteration 4:{space 3}log likelihood = {res:-2439.0963}  
Iteration 5:{space 3}log likelihood = {res:-2439.0915}  (backed up)
Iteration 6:{space 3}log likelihood = {res:-2439.0914}  (backed up)
Iteration 7:{space 3}log likelihood = {res:-2439.0913}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-2439.0913}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2439.0913}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 15:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 28:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 30:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 34:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 36:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 37:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 38:{space 2}log likelihood = {res:-2439.0913}  (backed up)
Iteration 39:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2439.0913}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2439.0912}  
Iteration 42:{space 2}log likelihood = {res:-2439.0903}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2439.0901}  
Iteration 44:{space 2}log likelihood = {res:-2439.0834}  
Iteration 45:{space 2}log likelihood = {res:-2439.0834}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2439.0834}  (backed up)
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3627
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     24.2
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   141.39
{txt}Log likelihood = {res}-2439.0834{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     china_threat{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}outgroup_h {c |}{col 19}{res}{space 2} .1878237{col 31}{space 2} .0158384{col 42}{space 1}   11.86{col 51}{space 3}0.000{col 59}{space 4}  .156781{col 72}{space 3} .2188664
{txt}{space 2}agri_proportion {c |}{col 19}{res}{space 2}-4.829432{col 31}{space 2} 1.873747{col 42}{space 1}   -2.58{col 51}{space 3}0.010{col 59}{space 4}-8.501909{col 72}{space 3}-1.156956
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .0557352{col 31}{space 2} .0408772{col 42}{space 1}    1.36{col 51}{space 3}0.173{col 59}{space 4}-.0243827{col 72}{space 3} .1358531
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum         {col 19}{c |}
        var(_cons){c |}{col 19}{res}{space 2} 4.05e-32{col 31}{space 2} 4.34e-17{col 59}{space 4}        .{col 72}{space 3}        .
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***This is a stronger effect***

. melogit china_threat $xlist_new2* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2027.7645}  
Iteration 1:{space 3}log likelihood = {res:-2026.0956}  
Iteration 2:{space 3}log likelihood = {res:-2026.0947}  
Iteration 3:{space 3}log likelihood = {res:-2026.0947}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res: -2094.658}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res: -2094.658}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2036.5669}  
Iteration 2:{space 3}log likelihood = {res:-2026.9813}  
Iteration 3:{space 3}log likelihood = {res:-2026.1784}  
Iteration 4:{space 3}log likelihood = {res:-2026.1085}  
Iteration 5:{space 3}log likelihood = {res:-2026.0999}  
Iteration 6:{space 3}log likelihood = {res:-2026.0974}  
Iteration 7:{space 3}log likelihood = {res:-2026.0969}  
Iteration 8:{space 3}log likelihood = {res:-2026.0968}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2026.0967}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2026.0967}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 27:{space 2}log likelihood = {res:-2026.0967}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 29:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 30:{space 2}log likelihood = {res:-2026.0967}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2026.0967}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2026.0967}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2026.0967}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2026.0967}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2026.0967}  (backed up)
Iteration 37:{space 2}log likelihood = {res:-2026.0966}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2026.0966}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2026.0966}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2026.0966}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2026.0966}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2026.0966}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2026.0966}  
Iteration 44:{space 2}log likelihood = {res:-2026.0952}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2026.0952}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2026.0952}  (not concave)
Iteration 47:{space 2}log likelihood = {res:-2026.0951}  
Iteration 48:{space 2}log likelihood = {res:-2026.0947}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2026.0947}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-2026.0947}  (not concave)
Iteration 51:{space 2}log likelihood = {res:-2026.0947}  (not concave)
Iteration 52:{space 2}log likelihood = {res:-2026.0947}  (backed up)
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3026
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     20.2
{col 64}{txt}max{col 68}={res}{col 70}       33

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   133.14
{txt}Log likelihood = {res}-2026.0947{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     china_threat{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}outgroup_h {c |}{col 19}{res}{space 2} .1891736{col 31}{space 2} .0195713{col 42}{space 1}    9.67{col 51}{space 3}0.000{col 59}{space 4} .1508145{col 72}{space 3} .2275326
{txt}{space 2}agri_proportion {c |}{col 19}{res}{space 2}-3.847357{col 31}{space 2} 2.084744{col 42}{space 1}   -1.85{col 51}{space 3}0.065{col 59}{space 4} -7.93338{col 72}{space 3} .2386651
{txt}{space 14}H15 {c |}{col 19}{res}{space 2}-.0155033{col 31}{space 2} .0066463{col 42}{space 1}   -2.33{col 51}{space 3}0.020{col 59}{space 4}-.0285297{col 72}{space 3}-.0024769
{txt}{space 12}B8OWN {c |}{col 19}{res}{space 2} .0417658{col 31}{space 2}   .01766{col 42}{space 1}    2.36{col 51}{space 3}0.018{col 59}{space 4} .0071528{col 72}{space 3} .0763789
{txt}{space 14}Age {c |}{col 19}{res}{space 2}-.0040003{col 31}{space 2} .0025933{col 42}{space 1}   -1.54{col 51}{space 3}0.123{col 59}{space 4}-.0090831{col 72}{space 3} .0010824
{txt}{space 15}H8 {c |}{col 19}{res}{space 2}-.0186191{col 31}{space 2} .0511608{col 42}{space 1}   -0.36{col 51}{space 3}0.716{col 59}{space 4}-.1188924{col 72}{space 3} .0816543
{txt}{space 11}degree {c |}{col 19}{res}{space 2} .1734781{col 31}{space 2} .0896184{col 42}{space 1}    1.94{col 51}{space 3}0.053{col 59}{space 4}-.0021707{col 72}{space 3} .3491269
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .2360398{col 31}{space 2} .1944728{col 42}{space 1}    1.21{col 51}{space 3}0.225{col 59}{space 4}-.1451199{col 72}{space 3} .6171994
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum         {col 19}{c |}
        var(_cons){c |}{col 19}{res}{space 2} 2.81e-35{col 31}{space 2} 3.89e-19{col 59}{space 4}        .{col 72}{space 3}        .
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***Doesn't quite hold up to the inclusion of more control variables***

. meologit F5CHINA $xlist_new1* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-3481.5703}  
Iteration 1:{space 3}log likelihood = {res:-3367.1092}  
Iteration 2:{space 3}log likelihood = {res:-3366.6086}  
Iteration 3:{space 3}log likelihood = {res:-3366.6084}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-3458.4449}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-3458.4449}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-3412.4594}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-3371.1041}  
Iteration 3:{space 3}log likelihood = {res:-3368.1958}  
Iteration 4:{space 3}log likelihood = {res:-3367.3455}  
Iteration 5:{space 3}log likelihood = {res:-3366.8744}  
Iteration 6:{space 3}log likelihood = {res:-3366.7227}  
Iteration 7:{space 3}log likelihood = {res:-3366.6594}  
Iteration 8:{space 3}log likelihood = {res:-3366.6521}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-3366.6503}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-3366.6494}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-3366.6492}  (backed up)
Iteration 12:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 13:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 14:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 15:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 16:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 17:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 18:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 19:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 20:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 21:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 22:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 23:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 24:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 25:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 26:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 27:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 28:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 29:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 30:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 31:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 32:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 33:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 34:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 35:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 36:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 37:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 38:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 39:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 40:{space 2}log likelihood = {res: -3366.649}  (not concave)
Iteration 41:{space 2}log likelihood = {res: -3366.649}  (backed up)
Iteration 42:{space 2}log likelihood = {res:-3366.6489}  (backed up)
Iteration 43:{space 2}log likelihood = {res:-3366.6489}  (backed up)
Iteration 44:{space 2}log likelihood = {res:-3366.6489}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-3366.6489}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-3366.6489}  
Iteration 47:{space 2}log likelihood = {res:-3366.6487}  (backed up)
Iteration 48:{space 2}log likelihood = {res:-3366.6481}  (backed up)
Iteration 49:{space 2}log likelihood = {res:-3366.6481}  (backed up)
Iteration 50:{space 2}log likelihood = {res:-3366.6456}  
Iteration 51:{space 2}log likelihood = {res:-3366.6456}  (backed up)
Iteration 52:{space 2}log likelihood = {res:-3366.6294}  
Iteration 53:{space 2}log likelihood = {res:-3366.6245}  
Iteration 54:{space 2}log likelihood = {res:-3366.6235}  
Iteration 55:{space 2}log likelihood = {res:-3366.6084}  (not concave)
Iteration 56:{space 2}log likelihood = {res:-3366.6084}  (not concave)
Iteration 57:{space 2}log likelihood = {res:-3366.6084}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3539
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     23.6
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   217.93
{txt}Log likelihood = {res}-3366.6084{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          F5CHINA{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}outgroup_h {c |}{col 19}{res}{space 2}-.2293227{col 31}{space 2} .0155386{col 42}{space 1}  -14.76{col 51}{space 3}0.000{col 59}{space 4}-.2597778{col 72}{space 3}-.1988677
{txt}{space 2}agri_proportion {c |}{col 19}{res}{space 2} 4.578429{col 31}{space 2} 1.822636{col 42}{space 1}    2.51{col 51}{space 3}0.012{col 59}{space 4} 1.006128{col 72}{space 3}  8.15073
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}/cut1 {c |}{col 19}{res}{space 2}-1.915907{col 31}{space 2} .0551024{col 42}{space 1}  -34.77{col 51}{space 3}0.000{col 59}{space 4}-2.023906{col 72}{space 3}-1.807908
{txt}{space 12}/cut2 {c |}{col 19}{res}{space 2} .1183802{col 31}{space 2} .0409343{col 42}{space 1}    2.89{col 51}{space 3}0.004{col 59}{space 4} .0381504{col 72}{space 3} .1986099
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum         {col 19}{c |}
        var(_cons){c |}{col 19}{res}{space 2} 3.94e-34{col 31}{space 2} 1.97e-18{col 59}{space 4}        .{col 72}{space 3}        .
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. meologit F5CHINA $xlist_new2* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2917.5184}  
Iteration 1:{space 3}log likelihood = {res:-2814.9954}  
Iteration 2:{space 3}log likelihood = {res:-2814.4942}  
Iteration 3:{space 3}log likelihood = {res: -2814.494}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2892.5465}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2892.5465}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2856.3319}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2822.8065}  
Iteration 3:{space 3}log likelihood = {res:-2814.8077}  
Iteration 4:{space 3}log likelihood = {res:-2814.6793}  
Iteration 5:{space 3}log likelihood = {res:-2814.6314}  
Iteration 6:{space 3}log likelihood = {res:-2814.5902}  
Iteration 7:{space 3}log likelihood = {res:-2814.5891}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-2814.5885}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2814.5885}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 27:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2814.5885}  (not concave)
Iteration 32:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 33:{space 2}log likelihood = {res:-2814.5885}  (backed up)
Iteration 34:{space 2}log likelihood = {res:-2814.5884}  (backed up)
Iteration 35:{space 2}log likelihood = {res:-2814.5884}  (not concave)
Iteration 36:{space 2}log likelihood = {res:-2814.5884}  
Iteration 37:{space 2}log likelihood = {res: -2814.588}  (not concave)
Iteration 38:{space 2}log likelihood = {res: -2814.588}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2814.5879}  
Iteration 40:{space 2}log likelihood = {res:-2814.5876}  (backed up)
Iteration 41:{space 2}log likelihood = {res:-2814.5847}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2814.5846}  
Iteration 43:{space 2}log likelihood = {res:-2814.5635}  
Iteration 44:{space 2}log likelihood = {res:-2814.5614}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2814.5609}  
Iteration 46:{space 2}log likelihood = {res: -2814.494}  (not concave)
Iteration 47:{space 2}log likelihood = {res: -2814.494}  (not concave)
Iteration 48:{space 2}log likelihood = {res: -2814.494}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     2974
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     19.8
{col 64}{txt}max{col 68}={res}{col 70}       30

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   193.99
{txt}Log likelihood = {res} -2814.494{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          F5CHINA{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}outgroup_h {c |}{col 19}{res}{space 2}-.2187573{col 31}{space 2} .0189493{col 42}{space 1}  -11.54{col 51}{space 3}0.000{col 59}{space 4}-.2558973{col 72}{space 3}-.1816173
{txt}{space 2}agri_proportion {c |}{col 19}{res}{space 2} 3.106871{col 31}{space 2} 2.017601{col 42}{space 1}    1.54{col 51}{space 3}0.124{col 59}{space 4}-.8475547{col 72}{space 3} 7.061296
{txt}{space 14}H15 {c |}{col 19}{res}{space 2} .0242175{col 31}{space 2} .0064242{col 42}{space 1}    3.77{col 51}{space 3}0.000{col 59}{space 4} .0116262{col 72}{space 3} .0368087
{txt}{space 12}B8OWN {c |}{col 19}{res}{space 2}-.0437525{col 31}{space 2} .0171021{col 42}{space 1}   -2.56{col 51}{space 3}0.011{col 59}{space 4}-.0772719{col 72}{space 3} -.010233
{txt}{space 14}Age {c |}{col 19}{res}{space 2} .0052432{col 31}{space 2} .0024959{col 42}{space 1}    2.10{col 51}{space 3}0.036{col 59}{space 4} .0003514{col 72}{space 3} .0101351
{txt}{space 15}H8 {c |}{col 19}{res}{space 2}-.0036524{col 31}{space 2} .0493967{col 42}{space 1}   -0.07{col 51}{space 3}0.941{col 59}{space 4}-.1004682{col 72}{space 3} .0931634
{txt}{space 11}degree {c |}{col 19}{res}{space 2}-.1935522{col 31}{space 2} .0856544{col 42}{space 1}   -2.26{col 51}{space 3}0.024{col 59}{space 4}-.3614318{col 72}{space 3}-.0256726
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}/cut1 {c |}{col 19}{res}{space 2}-1.652466{col 31}{space 2} .1920311{col 42}{space 1}   -8.61{col 51}{space 3}0.000{col 59}{space 4} -2.02884{col 72}{space 3}-1.276092
{txt}{space 12}/cut2 {c |}{col 19}{res}{space 2} .3877121{col 31}{space 2}  .189052{col 42}{space 1}    2.05{col 51}{space 3}0.040{col 59}{space 4} .0171769{col 72}{space 3} .7582473
{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum         {col 19}{c |}
        var(_cons){c |}{col 19}{res}{space 2} 6.72e-33{col 31}{space 2} 1.11e-17{col 59}{space 4}        .{col 72}{space 3}        .
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. ***Using exporter/importer ratio for good measure***

. global xlist1a outgroup_h exp_imp_ratio

. global xlist2a outgroup_h exp_imp_ratio H15 B8OWN Age H8 degree

. global xlist3a outgroup_h exp_imp_ratio H15 B8OWN Age H8 degree min_occ inter1

. melogit china_threat $xlist1a* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2443.0005}  
Iteration 1:{space 3}log likelihood = {res:-2441.0278}  
Iteration 2:{space 3}log likelihood = {res: -2441.027}  
Iteration 3:{space 3}log likelihood = {res: -2441.027}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2521.7258}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2521.7258}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2444.8909}  
Iteration 2:{space 3}log likelihood = {res:-2441.5888}  
Iteration 3:{space 3}log likelihood = {res:-2441.2353}  
Iteration 4:{space 3}log likelihood = {res:-2441.0841}  
Iteration 5:{space 3}log likelihood = {res:-2441.0453}  
Iteration 6:{space 3}log likelihood = {res:-2441.0306}  
Iteration 7:{space 3}log likelihood = {res:-2441.0302}  (backed up)
Iteration 8:{space 3}log likelihood = {res:  -2441.03}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-2441.0299}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 22:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 24:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 30:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 36:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 38:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2441.0299}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 41:{space 2}log likelihood = {res:-2441.0299}  (backed up)
Iteration 42:{space 2}log likelihood = {res:-2441.0298}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2441.0298}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2441.0298}  (backed up)
Iteration 45:{space 2}log likelihood = {res:-2441.0297}  
Iteration 46:{space 2}log likelihood = {res: -2441.027}  
Iteration 47:{space 2}log likelihood = {res: -2441.027}  
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3627
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     24.2
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   137.98
{txt}Log likelihood = {res} -2441.027{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   china_threat{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}outgroup_h {c |}{col 17}{res}{space 2} .1855265{col 29}{space 2} .0157956{col 40}{space 1}   11.75{col 49}{space 3}0.000{col 57}{space 4} .1545676{col 70}{space 3} .2164854
{txt}{space 2}exp_imp_ratio {c |}{col 17}{res}{space 2}-.0720813{col 29}{space 2}  .043261{col 40}{space 1}   -1.67{col 49}{space 3}0.096{col 57}{space 4}-.1568714{col 70}{space 3} .0127087
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  .036202{col 29}{space 2} .0413139{col 40}{space 1}    0.88{col 49}{space 3}0.381{col 57}{space 4}-.0447718{col 70}{space 3} .1171758
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum       {col 17}{c |}
      var(_cons){c |}{col 17}{res}{space 2} 7.75e-31{col 29}{space 2} 2.68e-16{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. melogit china_threat $xlist2a* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2028.1849}  
Iteration 1:{space 3}log likelihood = {res:-2026.5187}  
Iteration 2:{space 3}log likelihood = {res:-2026.5178}  
Iteration 3:{space 3}log likelihood = {res:-2026.5178}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2094.7512}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2094.7512}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2036.7361}  
Iteration 2:{space 3}log likelihood = {res:-2028.0477}  
Iteration 3:{space 3}log likelihood = {res: -2026.586}  
Iteration 4:{space 3}log likelihood = {res:-2026.5331}  
Iteration 5:{space 3}log likelihood = {res:-2026.5214}  
Iteration 6:{space 3}log likelihood = {res:-2026.5186}  
Iteration 7:{space 3}log likelihood = {res: -2026.518}  
Iteration 8:{space 3}log likelihood = {res:-2026.5179}  
Iteration 9:{space 3}log likelihood = {res:-2026.5179}  
Iteration 10:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 16:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 31:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 33:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2026.5179}  (not concave)
Iteration 35:{space 2}log likelihood = {res:-2026.5179}  (backed up)
Iteration 36:{space 2}log likelihood = {res:-2026.5178}  
Iteration 37:{space 2}log likelihood = {res:-2026.5178}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-2026.5178}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2026.5178}  (backed up)
Iteration 40:{space 2}log likelihood = {res:-2026.5178}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2026.5178}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2026.5178}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2026.5178}  (backed up)
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3026
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     20.2
{col 64}{txt}max{col 68}={res}{col 70}       33

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   132.39
{txt}Log likelihood = {res}-2026.5178{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   china_threat{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}outgroup_h {c |}{col 17}{res}{space 2} .1887579{col 29}{space 2} .0195703{col 40}{space 1}    9.65{col 49}{space 3}0.000{col 57}{space 4} .1504008{col 70}{space 3}  .227115
{txt}{space 2}exp_imp_ratio {c |}{col 17}{res}{space 2}-.0763868{col 29}{space 2} .0478058{col 40}{space 1}   -1.60{col 49}{space 3}0.110{col 57}{space 4}-.1700845{col 70}{space 3} .0173109
{txt}{space 12}H15 {c |}{col 17}{res}{space 2}-.0148306{col 29}{space 2} .0066263{col 40}{space 1}   -2.24{col 49}{space 3}0.025{col 57}{space 4}-.0278178{col 70}{space 3}-.0018433
{txt}{space 10}B8OWN {c |}{col 17}{res}{space 2} .0415482{col 29}{space 2} .0176551{col 40}{space 1}    2.35{col 49}{space 3}0.019{col 57}{space 4} .0069449{col 70}{space 3} .0761515
{txt}{space 12}Age {c |}{col 17}{res}{space 2}-.0040677{col 29}{space 2} .0025925{col 40}{space 1}   -1.57{col 49}{space 3}0.117{col 57}{space 4}-.0091489{col 70}{space 3} .0010136
{txt}{space 13}H8 {c |}{col 17}{res}{space 2}-.0180655{col 29}{space 2} .0511702{col 40}{space 1}   -0.35{col 49}{space 3}0.724{col 57}{space 4}-.1183573{col 70}{space 3} .0822263
{txt}{space 9}degree {c |}{col 17}{res}{space 2} .1747126{col 29}{space 2} .0896025{col 40}{space 1}    1.95{col 49}{space 3}0.051{col 57}{space 4}-.0009051{col 70}{space 3} .3503304
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2263336{col 29}{space 2}  .194181{col 40}{space 1}    1.17{col 49}{space 3}0.244{col 57}{space 4}-.1542542{col 70}{space 3} .6069215
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum       {col 17}{c |}
      var(_cons){c |}{col 17}{res}{space 2} 3.18e-27{col 29}{space 2} 2.05e-13{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. melogit china_threat $xlist3a* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2026.6571}  
Iteration 1:{space 3}log likelihood = {res:-2024.9751}  
Iteration 2:{space 3}log likelihood = {res:-2024.9743}  
Iteration 3:{space 3}log likelihood = {res:-2024.9743}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2092.8832}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2092.8832}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2035.0026}  
Iteration 2:{space 3}log likelihood = {res:-2026.9118}  
Iteration 3:{space 3}log likelihood = {res:-2025.0156}  
Iteration 4:{space 3}log likelihood = {res:-2024.9737}  
Iteration 5:{space 3}log likelihood = {res:-2024.9736}  
{res}
{txt}Mixed-effects logistic regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3026
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     20.2
{col 64}{txt}max{col 68}={res}{col 70}       33

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}9{txt}){col 68}={res}{col 70}   134.23
{txt}Log likelihood = {res}-2024.9736{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   china_threat{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}outgroup_h {c |}{col 17}{res}{space 2} .1893633{col 29}{space 2}  .019661{col 40}{space 1}    9.63{col 49}{space 3}0.000{col 57}{space 4} .1508284{col 70}{space 3} .2278982
{txt}{space 2}exp_imp_ratio {c |}{col 17}{res}{space 2}-.1002967{col 29}{space 2} .0549743{col 40}{space 1}   -1.82{col 49}{space 3}0.068{col 57}{space 4}-.2080444{col 70}{space 3}  .007451
{txt}{space 12}H15 {c |}{col 17}{res}{space 2}-.0138461{col 29}{space 2} .0066882{col 40}{space 1}   -2.07{col 49}{space 3}0.038{col 57}{space 4}-.0269548{col 70}{space 3}-.0007375
{txt}{space 10}B8OWN {c |}{col 17}{res}{space 2} .0418867{col 29}{space 2} .0176914{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0072122{col 70}{space 3} .0765611
{txt}{space 12}Age {c |}{col 17}{res}{space 2}-.0040199{col 29}{space 2} .0025954{col 40}{space 1}   -1.55{col 49}{space 3}0.121{col 57}{space 4}-.0091068{col 70}{space 3}  .001067
{txt}{space 13}H8 {c |}{col 17}{res}{space 2}-.0167063{col 29}{space 2} .0512236{col 40}{space 1}   -0.33{col 49}{space 3}0.744{col 57}{space 4}-.1171027{col 70}{space 3}   .08369
{txt}{space 9}degree {c |}{col 17}{res}{space 2} .1652164{col 29}{space 2} .0900016{col 40}{space 1}    1.84{col 49}{space 3}0.066{col 57}{space 4}-.0111834{col 70}{space 3} .3416162
{txt}{space 8}min_occ {c |}{col 17}{res}{space 2}-.1808053{col 29}{space 2} .1043844{col 40}{space 1}   -1.73{col 49}{space 3}0.083{col 57}{space 4} -.385395{col 70}{space 3} .0237843
{txt}{space 9}inter1 {c |}{col 17}{res}{space 2} 2.780806{col 29}{space 2}  3.34982{col 40}{space 1}    0.83{col 49}{space 3}0.406{col 57}{space 4} -3.78472{col 70}{space 3} 9.346332
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2610537{col 29}{space 2} .1956602{col 40}{space 1}    1.33{col 49}{space 3}0.182{col 57}{space 4}-.1224333{col 70}{space 3} .6445407
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum       {col 17}{c |}
      var(_cons){c |}{col 17}{res}{space 2} .0008176{col 29}{space 2} .0230836{col 57}{space 4} 7.57e-28{col 70}{space 3} 8.83e+20
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. logistic regression:{col 34}{txt}{help j_chibar##|_new:chibar2(01) =}{res}{col 48} 1.3e-03{col 57}{txt}Prob>=chibar2 = {res}{col 73}0.4858

{com}. ***Again the interaction term points in the wrong direction***

. meologit F5CHINA $xlist1a* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-3481.5703}  
Iteration 1:{space 3}log likelihood = {res:-3369.0636}  
Iteration 2:{space 3}log likelihood = {res:-3368.5875}  
Iteration 3:{space 3}log likelihood = {res:-3368.5873}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-3458.7916}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-3458.7916}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-3412.8429}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-3372.0966}  
Iteration 3:{space 3}log likelihood = {res:-3368.8644}  
Iteration 4:{space 3}log likelihood = {res:-3368.6651}  
Iteration 5:{space 3}log likelihood = {res:-3368.6292}  
Iteration 6:{space 3}log likelihood = {res:-3368.6271}  (backed up)
Iteration 7:{space 3}log likelihood = {res: -3368.627}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-3368.6269}  (backed up)
Iteration 9:{space 3}log likelihood = {res:-3368.6269}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 18:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 19:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 20:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 21:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 23:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 25:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 26:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 27:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 28:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 31:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 33:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 34:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 35:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 36:{space 2}log likelihood = {res:-3368.6269}  (backed up)
Iteration 37:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 38:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-3368.6269}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-3368.6268}  
Iteration 42:{space 2}log likelihood = {res:-3368.6256}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-3368.6255}  
Iteration 44:{space 2}log likelihood = {res:-3368.6231}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-3368.6227}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-3368.6223}  (not concave)
Iteration 47:{space 2}log likelihood = {res: -3368.622}  
Iteration 48:{space 2}log likelihood = {res:-3368.6069}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-3368.6061}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-3368.6055}  
Iteration 51:{space 2}log likelihood = {res:-3368.5873}  
Iteration 52:{space 2}log likelihood = {res:-3368.5873}  (not concave)
Iteration 53:{space 2}log likelihood = {res:-3368.5873}  (not concave)
Iteration 54:{space 2}log likelihood = {res:-3368.5873}  (not concave)
Iteration 55:{space 2}log likelihood = {res:-3368.5873}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     3539
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}       10
{col 64}{txt}avg{col 68}={res}{col 70}     23.6
{col 64}{txt}max{col 68}={res}{col 70}       36

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}2{txt}){col 68}={res}{col 70}   214.58
{txt}Log likelihood = {res}-3368.5873{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        F5CHINA{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}outgroup_h {c |}{col 17}{res}{space 2}-.2269061{col 29}{space 2} .0154952{col 40}{space 1}  -14.64{col 49}{space 3}0.000{col 57}{space 4}-.2572761{col 70}{space 3}-.1965361
{txt}{space 2}exp_imp_ratio {c |}{col 17}{res}{space 2}  .065914{col 29}{space 2} .0425705{col 40}{space 1}    1.55{col 49}{space 3}0.122{col 57}{space 4}-.0175226{col 70}{space 3} .1493506
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/cut1 {c |}{col 17}{res}{space 2}-1.934011{col 29}{space 2} .0557202{col 40}{space 1}  -34.71{col 49}{space 3}0.000{col 57}{space 4} -2.04322{col 70}{space 3}-1.824801
{txt}{space 10}/cut2 {c |}{col 17}{res}{space 2} .0986537{col 29}{space 2} .0414998{col 40}{space 1}    2.38{col 49}{space 3}0.017{col 57}{space 4} .0173157{col 70}{space 3} .1799918
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum       {col 17}{c |}
      var(_cons){c |}{col 17}{res}{space 2} 8.18e-35{col 29}{space 2} 1.26e-18{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48} 5.9e-11{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. meologit F5CHINA $xlist2a* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2917.5184}  
Iteration 1:{space 3}log likelihood = {res:-2815.5608}  
Iteration 2:{space 3}log likelihood = {res:-2815.0684}  
Iteration 3:{space 3}log likelihood = {res:-2815.0682}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2892.6857}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2892.6857}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2856.4807}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2823.0477}  
Iteration 3:{space 3}log likelihood = {res:-2815.8256}  
Iteration 4:{space 3}log likelihood = {res:-2815.3534}  
Iteration 5:{space 3}log likelihood = {res:-2815.1499}  
Iteration 6:{space 3}log likelihood = {res:-2815.1223}  
Iteration 7:{space 3}log likelihood = {res:-2815.1208}  (backed up)
Iteration 8:{space 3}log likelihood = {res:-2815.1201}  (backed up)
Iteration 9:{space 3}log likelihood = {res:  -2815.12}  (backed up)
Iteration 10:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 11:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 12:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 13:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 14:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 15:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 16:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 17:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 18:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 19:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 20:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 21:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 22:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 23:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 24:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 25:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 26:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 27:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 28:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 29:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 30:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 31:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 32:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 33:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 34:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 35:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 36:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 37:{space 2}log likelihood = {res:  -2815.12}  (not concave)
Iteration 38:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 39:{space 2}log likelihood = {res:  -2815.12}  (backed up)
Iteration 40:{space 2}log likelihood = {res:-2815.1198}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2815.1197}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2815.1197}  
Iteration 43:{space 2}log likelihood = {res:-2815.1193}  (backed up)
Iteration 44:{space 2}log likelihood = {res:-2815.1162}  (not concave)
Iteration 45:{space 2}log likelihood = {res:-2815.1159}  
Iteration 46:{space 2}log likelihood = {res:-2815.0951}  
Iteration 47:{space 2}log likelihood = {res:-2815.0682}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2815.0682}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2815.0682}  (backed up)
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     2974
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     19.8
{col 64}{txt}max{col 68}={res}{col 70}       30

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}7{txt}){col 68}={res}{col 70}   193.06
{txt}Log likelihood = {res}-2815.0682{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        F5CHINA{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}outgroup_h {c |}{col 17}{res}{space 2}-.2179429{col 29}{space 2} .0189385{col 40}{space 1}  -11.51{col 49}{space 3}0.000{col 57}{space 4}-.2550617{col 70}{space 3}-.1808241
{txt}{space 2}exp_imp_ratio {c |}{col 17}{res}{space 2} .0520388{col 29}{space 2} .0469246{col 40}{space 1}    1.11{col 49}{space 3}0.267{col 57}{space 4}-.0399317{col 70}{space 3} .1440094
{txt}{space 12}H15 {c |}{col 17}{res}{space 2} .0236234{col 29}{space 2} .0064047{col 40}{space 1}    3.69{col 49}{space 3}0.000{col 57}{space 4} .0110705{col 70}{space 3} .0361764
{txt}{space 10}B8OWN {c |}{col 17}{res}{space 2}-.0434944{col 29}{space 2} .0170939{col 40}{space 1}   -2.54{col 49}{space 3}0.011{col 57}{space 4}-.0769979{col 70}{space 3} -.009991
{txt}{space 12}Age {c |}{col 17}{res}{space 2}  .005283{col 29}{space 2} .0024953{col 40}{space 1}    2.12{col 49}{space 3}0.034{col 57}{space 4} .0003923{col 70}{space 3} .0101738
{txt}{space 13}H8 {c |}{col 17}{res}{space 2}-.0038972{col 29}{space 2} .0494023{col 40}{space 1}   -0.08{col 49}{space 3}0.937{col 57}{space 4}-.1007239{col 70}{space 3} .0929295
{txt}{space 9}degree {c |}{col 17}{res}{space 2}-.1949024{col 29}{space 2} .0856427{col 40}{space 1}   -2.28{col 49}{space 3}0.023{col 57}{space 4}-.3627589{col 70}{space 3}-.0270458
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/cut1 {c |}{col 17}{res}{space 2}-1.665824{col 29}{space 2} .1918313{col 40}{space 1}   -8.68{col 49}{space 3}0.000{col 57}{space 4}-2.041806{col 70}{space 3}-1.289841
{txt}{space 10}/cut2 {c |}{col 17}{res}{space 2} .3739601{col 29}{space 2} .1888072{col 40}{space 1}    1.98{col 49}{space 3}0.048{col 57}{space 4} .0039048{col 70}{space 3} .7440153
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum       {col 17}{c |}
      var(_cons){c |}{col 17}{res}{space 2} 3.52e-32{col 29}{space 2} 3.83e-17{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48}    0.00{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. meologit F5CHINA $xlist3a* ||DivisNum:
{res}{txt}
Fitting fixed-effects model:

Iteration 0:{space 3}log likelihood = {res:-2917.5184}  
Iteration 1:{space 3}log likelihood = {res:-2813.6814}  
Iteration 2:{space 3}log likelihood = {res:-2813.1731}  
Iteration 3:{space 3}log likelihood = {res:-2813.1729}  

Refining starting values:

Grid node 0:{space 3}log likelihood = {res:-2890.5014}

Fitting full model:
{res}
{txt}Iteration 0:{space 3}log likelihood = {res:-2890.5014}  (not concave)
Iteration 1:{space 3}log likelihood = {res:-2854.3381}  (not concave)
Iteration 2:{space 3}log likelihood = {res:-2820.9865}  
Iteration 3:{space 3}log likelihood = {res:-2814.1422}  
Iteration 4:{space 3}log likelihood = {res: -2813.549}  
Iteration 5:{space 3}log likelihood = {res:-2813.3078}  
Iteration 6:{space 3}log likelihood = {res:-2813.2461}  
Iteration 7:{space 3}log likelihood = {res:-2813.2227}  
Iteration 8:{space 3}log likelihood = {res:-2813.2175}  (backed up)
Iteration 9:{space 3}log likelihood = {res: -2813.215}  (backed up)
Iteration 10:{space 2}log likelihood = {res:-2813.2138}  (backed up)
Iteration 11:{space 2}log likelihood = {res:-2813.2136}  (backed up)
Iteration 12:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 13:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 14:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 15:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 16:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 17:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 18:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 19:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 20:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 21:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 22:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 23:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 24:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 25:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 26:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 27:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 28:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 29:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 30:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 31:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 32:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 33:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 34:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 35:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 36:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 37:{space 2}log likelihood = {res:-2813.2135}  (backed up)
Iteration 38:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 39:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 40:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 41:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 42:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 43:{space 2}log likelihood = {res:-2813.2135}  (not concave)
Iteration 44:{space 2}log likelihood = {res:-2813.2135}  
Iteration 45:{space 2}log likelihood = {res:-2813.2132}  (not concave)
Iteration 46:{space 2}log likelihood = {res:-2813.2131}  (not concave)
Iteration 47:{space 2}log likelihood = {res: -2813.213}  (not concave)
Iteration 48:{space 2}log likelihood = {res:-2813.2128}  (not concave)
Iteration 49:{space 2}log likelihood = {res:-2813.2123}  (not concave)
Iteration 50:{space 2}log likelihood = {res:-2813.2116}  
Iteration 51:{space 2}log likelihood = {res:-2813.1729}  
Iteration 52:{space 2}log likelihood = {res:-2813.1729}  
{res}
{txt}Mixed-effects ologit regression{col 49}{txt}Number of obs{col 68}={res}{col 70}     2974
{txt}Group variable: {col 24}{res}DivisNum{col 49}{txt}Number of groups{col 68}={res}{col 70}      150

{col 49}{txt}Obs per group: min{col 68}={res}{col 70}        8
{col 64}{txt}avg{col 68}={res}{col 70}     19.8
{col 64}{txt}max{col 68}={res}{col 70}       30

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration points ={col 78}{res}7

{col 49}{txt}Wald chi2({res}9{txt}){col 68}={res}{col 70}   196.64
{txt}Log likelihood = {res}-2813.1729{col 49}{txt}Prob > chi2{col 68}={res}{col 73}0.0000
{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        F5CHINA{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}outgroup_h {c |}{col 17}{res}{space 2}-.2179722{col 29}{space 2} .0189813{col 40}{space 1}  -11.48{col 49}{space 3}0.000{col 57}{space 4}-.2551749{col 70}{space 3}-.1807695
{txt}{space 2}exp_imp_ratio {c |}{col 17}{res}{space 2} .0865864{col 29}{space 2} .0537208{col 40}{space 1}    1.61{col 49}{space 3}0.107{col 57}{space 4}-.0187044{col 70}{space 3} .1918771
{txt}{space 12}H15 {c |}{col 17}{res}{space 2} .0227553{col 29}{space 2} .0064448{col 40}{space 1}    3.53{col 49}{space 3}0.000{col 57}{space 4} .0101237{col 70}{space 3} .0353869
{txt}{space 10}B8OWN {c |}{col 17}{res}{space 2}-.0438819{col 29}{space 2} .0171114{col 40}{space 1}   -2.56{col 49}{space 3}0.010{col 57}{space 4}-.0774197{col 70}{space 3} -.010344
{txt}{space 12}Age {c |}{col 17}{res}{space 2} .0051935{col 29}{space 2} .0024966{col 40}{space 1}    2.08{col 49}{space 3}0.038{col 57}{space 4} .0003002{col 70}{space 3} .0100868
{txt}{space 13}H8 {c |}{col 17}{res}{space 2}-.0049176{col 29}{space 2}  .049433{col 40}{space 1}   -0.10{col 49}{space 3}0.921{col 57}{space 4}-.1018045{col 70}{space 3} .0919693
{txt}{space 9}degree {c |}{col 17}{res}{space 2}-.1867915{col 29}{space 2} .0859352{col 40}{space 1}   -2.17{col 49}{space 3}0.030{col 57}{space 4}-.3552213{col 70}{space 3}-.0183617
{txt}{space 8}min_occ {c |}{col 17}{res}{space 2} .1947653{col 29}{space 2} .1004158{col 40}{space 1}    1.94{col 49}{space 3}0.052{col 57}{space 4}-.0020461{col 70}{space 3} .3915768
{txt}{space 9}inter1 {c |}{col 17}{res}{space 2}-4.144839{col 29}{space 2} 3.254005{col 40}{space 1}   -1.27{col 49}{space 3}0.203{col 57}{space 4}-10.52257{col 70}{space 3} 2.232893
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}/cut1 {c |}{col 17}{res}{space 2}-1.631716{col 29}{space 2} .1926299{col 40}{space 1}   -8.47{col 49}{space 3}0.000{col 57}{space 4}-2.009263{col 70}{space 3}-1.254168
{txt}{space 10}/cut2 {c |}{col 17}{res}{space 2} .4101829{col 29}{space 2} .1897648{col 40}{space 1}    2.16{col 49}{space 3}0.031{col 57}{space 4} .0382508{col 70}{space 3} .7821149
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DivisNum       {col 17}{c |}
      var(_cons){c |}{col 17}{res}{space 2} 9.65e-31{col 29}{space 2} 3.64e-16{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{txt}LR test vs. ologit regression:{col 38}{txt}chi2({res}0{txt}) ={res}{col 48} 1.0e-10{col 59}{txt}Prob > chi2 ={res}{col 73}     .

{txt}{p 0 6 4}Note: {help j_mixedlr##|_new:LR test is conservative} and provided only for reference.{p_end}

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}\\cap\coombs\IPS1\redirections\u5390570\Desktop\Australian Public Opinion and Foreign Policy\Public Opinion on China Paper\IRAP Resubmission\Reanalysis of the Results.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}20 Oct 2015, 14:37:33
{txt}{.-}
{smcl}
{txt}{sf}{ul off}